Pricing of new products using Fuzzy Expert System: a case study in glass industry
Subject Areas : Journal of Investment Knowledge
M. E. Mohammad Pourzarandi
1
(دانشیار و عضوهیأت علمی دانشکده مدیریت،دانشگاه آزاد اسلامی واحد تهران مرکز)
Arefe Fadavi Asghari
2
(استادیار وعضوهیأت علمی دانشکده مدیریت،دانشگاه آزاد اسلامی واحد تهران مرکز)
Atiye Jafarian
3
(دانشجوی کارشناسی ارشد، مدیریت صنعتی (تحقیق در عملیات)، دانشگاه آزاد اسلامی واحد تهران مرکز)
Keywords: Fuzzy expert system, Fuzzy Inference System,
Abstract :
Nowadays, the world is become as an arena for different producers, companies and manufacturers to compete with each other in different area as a rat race. Meanwhile, the winner is the one who has achieved a greater market share. Consequently, measures such as proper pricing for available products and new products can pave the ground for achieving to a more market share. In this regard, many companies have focused on their products price to achieve a more success through scientific methods in the competition market. Accordingly, in this paper, the potential pricing factors that can be useful in determining the new products price were collected from the credible research and books that these factors are: supplement or substitute goods, life cycle, brand, adaptation, threat of entrance, marketing strategy, consumer awareness, expected value of customer and risk. Then, a questionnaire was prepared and delivered among pricing experts of Glass Industry. Subsequently, the effective factors were chosen through statistical hypotheses. In addition, a fuzzy inference system (FIS) was designed based on the collected rules that govern in this industry for new developed products pricing. Then, the results lead to price index for new product (α). Furthermore, the sale price was forecasted based on the price index resulted from FIS and prime cost. To check the capability of this research, the model efficiency was studied in Mina Glass Country as a real case study. At the end, the possible profit was studied by comparing suggested price with current sale price as a model efficiency confirmation.
